PROJECT SUMMARY/ABSTRACT Although the general population continues to be at risk of exposure to ionizing radiation because of nuclear warfare, terrorism, or radiological accidents, there are currently no biomarker assays that are predictive of radiation-induced late injury in specific organs. In cases of heterogeneous exposures and for victims who survive the acute effects, there will be a latent period of months to decades before serious symptoms manifest. This proposal brings together an inter-disciplinary research team with expertise in radiation biology, animal models of tissue injury, biomarker development, biostatistics and bioinformatics to identify analytically validated rapid and minimally invasive assays that predict delayed radiation injury in different organ systems. Discovery and validation of radiation biomarkers are based on the underlying premises that: 1) a signature of radiation exposure is present in biofluids (plasma and urine) at some point prior to clinical diagnosis; and 2) early diagnosis can result in improved clinical care and outcome. Using a discovery-validation study design, we propose to identify metabolic biomarkers of radiation injury to three major organs at risk for delayed complications: kidney, heart and brain (Specific Aim 1), and develop a kit-based assay along with a biomarker scoring algorithm for assessing and predicting injury in these organs (Specific Aim 2). We will make use of our established rat models of partial and total body irradiation to identify plasma and urine biomarkers that predict the extent of injury in the kidney, heart and brain before clinical symptoms appear. For this purpose, we will make use of male and female rats of an inbred and an outbred strain and expose rats to X-rays and a mixed neutron/?-ray beam. We will determine which matrix (plasma or urine) provides the best predictor for each of the organ systems. We will validate rat biomarker panels in independent cohorts of rats and in banked samples of non-human primates exposed to radiation. Biomarker panels will then be used to develop a prototype metabolite kit in 96-well format and test its technical feasibility in accordance with good laboratory practice guidelines. This prototype kit is required for the rapid future development of a field-deployable minimally invasive biomarker assay that will identify individuals at risk. At the conclusion of these studies, we expect to delineate minimally invasive, high specificity classification algorithms for predicting delayed radiation injuries in kidney, heart and brain with >90% specificity, sensitivity, and positive predictive value. While here we focus on radiation late effects, the standard operating procedures, assay parameters and decision analysis software developed in this study will serve as a foundation for broader based implementation of minimally invasive biomarkers in radiation risk assessment.